The field of the invention is systems and methods for magnetic resonance imaging (“MRI”). More particularly, the invention relates to systems and methods for motion correction in MRI.
When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field B0), the individual magnetic moments of the nuclei in the tissue attempt to align with this polarizing field, but precess about it in random order at their characteristic Larmor frequency. If the substance, or tissue, is subjected to a magnetic field (excitation field B1) that is in the x-y plane and that is near the Larmor frequency, the net aligned moment, Mz, may be rotated, or “tipped,” into the x-y plane to produce a net transverse magnetic moment Mxy. A signal is emitted by the excited nuclei or “spins,” after the excitation signal B1 is terminated, and this signal may be received and processed to form an image.
When utilizing these “MR” signals to produce images, magnetic field gradients (Gx, Gy, and Gz) are employed. Typically, the region to be imaged is scanned by a sequence of measurement cycles in which these gradients vary according to the particular localization method being used. The resulting set of received MR signals are digitized and processed to reconstruct the image using one of many well known reconstruction techniques.
The measurement cycle used to acquire each MR signal is performed under the direction of a pulse sequence produced by a pulse sequencer. Clinically available MRI systems store a library of such pulse sequences that can be prescribed to meet the needs of many different clinical applications. Research MRI systems include a library of clinically-proven pulse sequences and they also enable the development of new pulse sequences.
The MR signals acquired with an MRI system are signal samples of the subject of the examination in Fourier space, or what is often referred to in the art as “k-space.” Each MR measurement cycle, or pulse sequence, typically samples a portion of k-space along a sampling trajectory characteristic of that pulse sequence. Most pulse sequences sample k-space in a raster scan-like pattern sometimes referred to as a “spin-warp,” a “Fourier,” a “rectilinear,” or a “Cartesian” scan. The spin-warp scan technique employs a variable amplitude phase encoding magnetic field gradient pulse prior to the acquisition of MR spin-echo signals to phase encode spatial information in the direction of this gradient. In a two-dimensional implementation (“2DFT”), for example, spatial information is encoded in one direction by applying a phase encoding gradient, Gy, along that direction, and then a spin-echo signal is acquired in the presence of a readout magnetic field gradient, Gx, in a direction orthogonal to the phase encoding direction. The readout gradient present during the spin-echo acquisition encodes spatial information in the orthogonal direction. In a typical 2DFT pulse sequence, the magnitude of the phase encoding gradient pulse, Gy, is incremented, ΔGy, in the sequence of measurement cycles, or “views” that are acquired during the scan to produce a set of k-space MR data from which an entire image can be reconstructed.
There are many other k-space sampling patterns used by MRI systems. These include “radial,” or “projection reconstruction” scans in which k-space is sampled as a set of radial sampling trajectories extending from the center of k-space. The pulse sequences for a radial scan are characterized by the lack of a phase encoding gradient and the presence of a readout gradient that changes direction from one pulse sequence view to the next. There are also many k-space sampling methods that are closely related to the radial scan and that sample along a curved k-space sampling trajectory rather than the straight line radial trajectory.
An image is reconstructed from the acquired k-space data by transforming the k-space data set to an image space data set. There are many different methods for performing this task and the method used is often determined by the technique used to acquire the k-space data. With a Cartesian grid of k-space data that results from a 2D or 3D spin-warp acquisition, for example, the most common reconstruction method used is an inverse Fourier transformation (“2DFT” or “3DFT”) along each of the 2 or 3 axes of the data set. With a radial k-space data set and its variations, the most common reconstruction method includes “regridding” the k-space samples to create a Cartesian grid of k-space samples and then performing a 2DFT or 3DFT on the regridded k-space data set. In the alternative, a radial k-space data set can also be transformed to Radon space by performing a 1DFT of each radial projection view and then transforming the Radon space data set to image space by performing a filtered backprojection.
Depending on the technique used, many MR scans currently used to produce medical images require many minutes to acquire the necessary data. The reduction of this scan time is an important consideration, since reduced scan time increases patient throughout, improves patient comfort, and improves image quality by reducing motion artifacts. Many different strategies have been developed to shorten the scan time.
One such strategy is referred to generally as “parallel imaging.” Parallel imaging techniques use spatial information from arrays of radio frequency (“RF”) receiver coils to substitute for the encoding that would otherwise have to be obtained in a sequential fashion using RF pulses and field gradient, such as, for example, phase and frequency encoding. Each of the spatially independent receiver coils of the array carries certain spatial information and has a different sensitivity profile. This information is utilized in order to achieve a complete location encoding of the received MR signals by a combination of the simultaneously acquired data received from the separate coils. Specifically, parallel imaging techniques undersample k-space by reducing the number of acquired phase-encoded k-space sampling lines while keeping the maximal extent covered in k-space fixed. The combination of the separate MR signals produced by the separate receiver coils enables a reduction of the acquisition time required for an image, in comparison to conventional k-space data acquisition, by a factor that, in the most favorable case, equals the number of the receiver coils. Thus the use of multiple receiver coils acts to multiply imaging speed, without increasing gradient switching rates or RF power.
Because it requires time to acquire a complete k-space MR data set, subject motion presents a problem in many clinical applications. Motion due to respiration, cardiac motion, or peristalsis can produce image artifacts such as blurring or ghosting. There are many strategies used to suppress such artifacts. These include cardiac or respiratory gating techniques that acquire MR data only during certain phases of the cardiac or respiratory cycle. The subject is thus scanned while in a particular position, but the overall scan time is increased substantially because MR data is not acquired over substantial portions of each motion cycle.
Another technique for dealing with subject motion is to interleave so-called “navigator” pulse sequences into the scan to measure subject motion. Navigator pulse sequences may be used during a scan to periodically acquire subject motion information with which the acquired k-space MR image data may be retrospectively corrected. Such navigator data may also be used to alter scanner operation to prospectively correct for subject motion. In either case, the interleaved navigator pulse sequences can add considerable scan time and in some cases they can disrupt the magnetization equilibrium required by imaging pulse sequences.
Two types of subject motion commonly exist when imaging a subject with MRI. These include rigid motion, including bulk translation and rotation; and non-rigid motion, including cardiac and respiratory motion. Numerous motion compensation methods have been proposed to address these sources of subject motion, including navigator echo methods; radial self-navigation methods; PROPELLER methods, such as those described by J. Pipe in “Motion Correction with PROPELLER MRI: Application to Head Motion and Freebreathing Cardiac Imaging,” Magnetic Resonance in Medicine, 1999; 42(5):963-969; general matrix inversion methods, such as those described by P. G. Batchelor, et al., in “Matrix Description of General Motion Correction Applied to Multishot Images,” Magnetic Resonance in Medicine, 2005; 54(5):1273-1280; and projection-based self-gating methods, such as those described by P. Lai, et al., in “A Respiratory Self-Gating Technique with 3D-Translation Compensation for Free-Breathing Whole-Heart Coronary MRA,” Magnetic Resonance in Medicine, 2009; 62(3):731-738.
The use of multi-coil arrays to accelerate image acquisition using parallel imaging presents the opportunity to use the redundant information provided by coil arrays for motion estimation and correction. For example, it has been shown that a generalized SMASH technique can be employed to predict a k-space line using previously acquired adjacent lines, as described by M. Bydder, et al., in “SMASH Navigators,” Magnetic Resonance in Medicine, 2003; 49(3):493-500. In this method, the predicted k-space line is compared with the actual acquired k-space line and the difference is used to correct for two-dimensional translations. However, this method does not correct for common imaging scenario where the body and coil array have relative motion, such as, in brain imaging applications using a rigid brain coil or in cardiac imaging applications with static posterior coil elements.
In another method, such as the one described by R. Bammer, et al., in “Augmented Generalized SENSE Reconstruction to Correct for Rigid Body Motion,” Magnetic Resonance in Medicine, 2007; 57(1):90-102, the bulk motion parameters (translation and rotation) were integrated into an iterative SENSE method, such as the one described by K. P. Pruessmann, et al., in “Advances in Sensitivity Encoding with Arbitrary k-Space Trajectories,” Magnetic Resonance in Medicine, 2001; 46(4):638-651, in order to correct for motion effects. In this method, the motion parameters are estimated from separately acquired, low-resolution navigator images using a similarity measure. For the most commonly used Cartesian sampling, the time required to acquire the navigator images is likely prohibitively long because they need to be acquired for every imaging shot.
In yet another method, such as the one described by D. Atkinson, et al., in “Coil-Based Artifact Reduction,” Magnetic Resonance in Medicine, 2004; 52(4):825-830, a separate uniform image for each coil is estimated using a generalized SMASH method that integrates motion parameters into the reconstruction and compares them with ones estimated from all the coils. In this method, the motion parameters that minimize the differences are chosen as the estimated motion.
For cardiac and respiratory motion, accurately resolving the amount of motion is more difficult because these types of motion are typically non-rigid. Currently, the method most widely recognized as being successful for cardiac motion compensation is electrocardiogram (“ECG”) gating. In addition, navigator-based methods have been successful for respiratory motion compensation in cardiac imaging applications. Recently, various cardiac and respiratory self-gating methods have been developed to remove the need for ECG signals, breath-holding, or navigator echoes. In one such method, such as the one described by T. A. Spraggins in “Wireless Retrospective Gating: Application to Cine Cardiac Imaging,” Magnetic Resonance Imaging, 1990; 8(6):675-681, a surrogate ECG signal is derived by monitoring the k-space center peak signal. This concept was extended in a radial imaging cardiac self-gating method, such as the one described by A. C. Larson, et al., in “Self-Gated Cardiac Cine MRI,” Magnetic Resonance in Medicine, 2004; 51(1):93-102, in which k-space peak magnitude, center of mass (“COM”), and a series of low-resolution navigator images are utilized to estimate motion. Similar methods with radial sampling have also been applied to respiratory self-gating, such as the one described by P. Lai, et al., in “A Dual-Projection Respiratory Self-Gating Technique for Whole-Heart Coronary MRA,” Journal of Magnetic Resonance Imaging, 2008; 28(3):612-620. Such self-gating methods use the signal from a single coil or combine multiple coil signals into a single composite signal.
With multiple receiver coil arrays commonly used in parallel imaging, each coil has localized sensitivity profiles. Thus, motion of the object relative to the coils causes variations in the received signal. The amount and polarity of these variations are different among the coils depending on the geometric configuration of each coil.
It would therefore be advantageous to provide a method for motion estimation and compensation that does not require the acquisition of time-intensive navigators and in which three-dimensional motion can be resolved without the acquisition of significant additional image data.